The steel turnout is one of the key components in the medium–low-speed maglev line system.However,the vehicle under active control is prone to vehicle–turnout coupled vibration,and thus,it is necessary to identify t...The steel turnout is one of the key components in the medium–low-speed maglev line system.However,the vehicle under active control is prone to vehicle–turnout coupled vibration,and thus,it is necessary to identify the vibration characteristics of this coupled system through field tests.To this end,dynamic performance tests were conducted on a vehicle–turnout coupled system in a medium–low-speed maglev test line.Firstly,the dynamic response data of the coupled system under various operating conditions were obtained.Then,the natural vibration characteristics of the turnout were analysed using the free attenuation method and the finite element method,indicating a good agreement between the simulation results and the measured results;the acceleration response characteristics of the coupled system were analysed in detail,and the ride quality of the vehicle was assessed by Sperling index.Finally,the frequency distribution characteristics of the coupled system were discussed.All these test results could provide references for model validation and optimized design of medium–low-speed maglev transport systems.展开更多
人机共驾阶段人类驾驶员对驾驶环境保持较高的风险感知水平是保证及时有效、稳定安全接管的核心。本研究通过开展风险感知模拟驾驶试验,获取了驾驶员在典型汽车-动力两轮车碰撞场景下的驾驶行为及脑电响应数据。从驾驶行为层面以制动TTC...人机共驾阶段人类驾驶员对驾驶环境保持较高的风险感知水平是保证及时有效、稳定安全接管的核心。本研究通过开展风险感知模拟驾驶试验,获取了驾驶员在典型汽车-动力两轮车碰撞场景下的驾驶行为及脑电响应数据。从驾驶行为层面以制动TTC(time to collision)和平均加速度为评价指标,利用分位数回归构建了驾驶员风险感知量化模型,通过独立样本检验发现驾驶经验、碰撞场景类型对驾驶员风险感知存在显著影响。在脑电响应层面,通过双独立样本检验及FDR校正发现Alpha频段与驾驶员风险感知显著相关。此外,提出了驾驶员风险感知神经机理,包括视觉感知与认知加工两个阶段。研究结果有助于提升人机共驾汽车的安全性。展开更多
In past terrorist attacks, vehicle borne improvised explosive devices (VBIED) have been the primary manner of attacking buildings and infrastructures. Preventing unauthorized vehicles from approaching a protected area...In past terrorist attacks, vehicle borne improvised explosive devices (VBIED) have been the primary manner of attacking buildings and infrastructures. Preventing unauthorized vehicles from approaching a protected area with anti-ram systems would maintain an established standoff distance against moving and stationary vehicles and consequently reduce blast and debris threats. This strategy has been considered the first line of defence against terrorists. Several types of anti-ram devices have been developed in accordance with U. S. Department of State K-rating criteria, for example, wedge barriers, rising beams, sliding/swing gates, and drop arms. However, these devices typically need a deep foundation for installation and can't be implemented into many locations where a depth of excavation is limited in order to protect utility lines of buildings and infrastructures. This paper presents a recent development of a series of shallow footing anti-ram bollard systems (SFABS) that can satisfy K-12 rating with only five-inch thick footing. A high-fidelity physics based finite element technique with a vehicle crash model is used for predicting anti-ram capacity and determining design parameters of the SFABS. Full-scale vehicle crash tests of the developed SFABS systems have been carried out to validate the design and analysis.展开更多
Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other a...Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other approaches, such as the discriminant analysis which requires these assumptions to be met. Moreover, it produces sound estimates by changing the probability range between 0.0 and 1.0 to log odds ranging from negative infinity to positive infinity, as it applies transformation of the dependent variable to a continuous variable. The estimates are asymptotically consistent with the requirements of the nonlinear regression process. The results of MNL can be interpreted by both the regression coefficient estimates and/or the odd ratios (the exponentiated coefficients) as well. In addition, the MNL can be used to improve the fitted model by comparing the full model that includes all predictors to a chosen restricted model by excluding the non-significant predictors. As such, this paper presents a detailed step by step overview of incorporating the MNL in crash severity modeling, using vehicle crash data of the Interstate I70 in the State of Missouri, USA for the years (2013-2015).展开更多
We investigate how a firm’s corporate pledgeable asset ownership(CPAO)affects the risk of future stock price crashes.Using pledgeable asset ownership and crash risk data for a large sample of U.S.firms,we provide nov...We investigate how a firm’s corporate pledgeable asset ownership(CPAO)affects the risk of future stock price crashes.Using pledgeable asset ownership and crash risk data for a large sample of U.S.firms,we provide novel empirical evidence that a firm’s risk of a future stock price crash decreases with an increase in its pledgeable assets.Our main findings are valid after conducting various robustness tests.Further channel tests reveal that firms with pledgeable assets increase their collateral value,thereby enhancing corporate transparency and limiting bad news hoarding,resulting in lower stock price crash risk.Overall,the results show that having more pledgeable assets enables easier access to external financing,making it less likely that managers will hoard bad news.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant No.51875483)the Independently Funded Research Project of State Key Laboratory of Traction Power(Grant Nos.2020TPL-T01 and 2020TPL-T04).
文摘The steel turnout is one of the key components in the medium–low-speed maglev line system.However,the vehicle under active control is prone to vehicle–turnout coupled vibration,and thus,it is necessary to identify the vibration characteristics of this coupled system through field tests.To this end,dynamic performance tests were conducted on a vehicle–turnout coupled system in a medium–low-speed maglev test line.Firstly,the dynamic response data of the coupled system under various operating conditions were obtained.Then,the natural vibration characteristics of the turnout were analysed using the free attenuation method and the finite element method,indicating a good agreement between the simulation results and the measured results;the acceleration response characteristics of the coupled system were analysed in detail,and the ride quality of the vehicle was assessed by Sperling index.Finally,the frequency distribution characteristics of the coupled system were discussed.All these test results could provide references for model validation and optimized design of medium–low-speed maglev transport systems.
文摘人机共驾阶段人类驾驶员对驾驶环境保持较高的风险感知水平是保证及时有效、稳定安全接管的核心。本研究通过开展风险感知模拟驾驶试验,获取了驾驶员在典型汽车-动力两轮车碰撞场景下的驾驶行为及脑电响应数据。从驾驶行为层面以制动TTC(time to collision)和平均加速度为评价指标,利用分位数回归构建了驾驶员风险感知量化模型,通过独立样本检验发现驾驶经验、碰撞场景类型对驾驶员风险感知存在显著影响。在脑电响应层面,通过双独立样本检验及FDR校正发现Alpha频段与驾驶员风险感知显著相关。此外,提出了驾驶员风险感知神经机理,包括视觉感知与认知加工两个阶段。研究结果有助于提升人机共驾汽车的安全性。
文摘In past terrorist attacks, vehicle borne improvised explosive devices (VBIED) have been the primary manner of attacking buildings and infrastructures. Preventing unauthorized vehicles from approaching a protected area with anti-ram systems would maintain an established standoff distance against moving and stationary vehicles and consequently reduce blast and debris threats. This strategy has been considered the first line of defence against terrorists. Several types of anti-ram devices have been developed in accordance with U. S. Department of State K-rating criteria, for example, wedge barriers, rising beams, sliding/swing gates, and drop arms. However, these devices typically need a deep foundation for installation and can't be implemented into many locations where a depth of excavation is limited in order to protect utility lines of buildings and infrastructures. This paper presents a recent development of a series of shallow footing anti-ram bollard systems (SFABS) that can satisfy K-12 rating with only five-inch thick footing. A high-fidelity physics based finite element technique with a vehicle crash model is used for predicting anti-ram capacity and determining design parameters of the SFABS. Full-scale vehicle crash tests of the developed SFABS systems have been carried out to validate the design and analysis.
文摘Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other approaches, such as the discriminant analysis which requires these assumptions to be met. Moreover, it produces sound estimates by changing the probability range between 0.0 and 1.0 to log odds ranging from negative infinity to positive infinity, as it applies transformation of the dependent variable to a continuous variable. The estimates are asymptotically consistent with the requirements of the nonlinear regression process. The results of MNL can be interpreted by both the regression coefficient estimates and/or the odd ratios (the exponentiated coefficients) as well. In addition, the MNL can be used to improve the fitted model by comparing the full model that includes all predictors to a chosen restricted model by excluding the non-significant predictors. As such, this paper presents a detailed step by step overview of incorporating the MNL in crash severity modeling, using vehicle crash data of the Interstate I70 in the State of Missouri, USA for the years (2013-2015).
基金supported by Institute for Information and communications Technology Planning and Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2017-0-01779,A machine learning and statistical inference frame-work for explainable artificial intelligence).
文摘We investigate how a firm’s corporate pledgeable asset ownership(CPAO)affects the risk of future stock price crashes.Using pledgeable asset ownership and crash risk data for a large sample of U.S.firms,we provide novel empirical evidence that a firm’s risk of a future stock price crash decreases with an increase in its pledgeable assets.Our main findings are valid after conducting various robustness tests.Further channel tests reveal that firms with pledgeable assets increase their collateral value,thereby enhancing corporate transparency and limiting bad news hoarding,resulting in lower stock price crash risk.Overall,the results show that having more pledgeable assets enables easier access to external financing,making it less likely that managers will hoard bad news.
